Fast and user-friendly multi-spectra Mueller matrix polarimeter for fresh tissue biopsy imaging

Mueller Matrix polarimetry (MMP) characterizes changes in light polarization after interacting with a medium, providing insights into tissue microstructure. Combined with multispectral (MS) imaging cameras, MS-MMP offers a novel way to quickly and safely acquire tissue surface information. Machine learning methodologies enable new diagnostic methods by automating tasks on fresh tissue biopsies, though this requires extensive and diverse data. To achieve this, we propose a user-friendly MS-MMP imager with a simple interface and fast acquisition time operated by laboratory technicians and residents. We show that our system, when operated by laboratory staff over several months, yields highquality data in large amounts and with positive feedback of its inclusion in a clinically compliant workflow. This positive outcome is promising for such systems to be used for large data collection initiatives.

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Publication Details

Journal
Open Access CRIS of the University of Bern
Published
2025-09-01
DOI
https://doi.org/10.48620/92284
Primary Topic
Optical Polarization and Ellipsometry
Type
article
Field-Weighted Citation Impact
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article

Fast and user-friendly multi-spectra Mueller matrix polarimeter for fresh tissue biopsy imaging

Open Access CRIS of the University of Bern
Optical Polarization and Ellipsometry
article

Fast and user-friendly multi-spectra Mueller matrix polarimeter for fresh tissue biopsy imaging

article en

Abstract

Mueller Matrix polarimetry (MMP) characterizes changes in light polarization after interacting with a medium, providing insights into tissue microstructure. Combined with multispectral (MS) imaging cameras, MS-MMP offers a novel way to quickly and safely acquire tissue surface information. Machine learning methodologies enable new diagnostic methods by automating tasks on fresh tissue biopsies, though this requires extensive and diverse data. To achieve this, we propose a user-friendly MS-MMP imager with a simple interface and fast acquisition time operated by laboratory technicians and residents. We show that our system, when operated by laboratory staff over several months, yields highquality data in large amounts and with positive feedback of its inclusion in a clinically compliant workflow. This positive outcome is promising for such systems to be used for large data collection initiatives.

Open Access CRIS of the University of Bern
United Nations Human Settlements Programme (KE), Tracer Technologies (United States) (US), Artificial Intelligence in Medicine (Canada) (CA), Tissue Genetics (United States) (US)
Openalex Percentile: Top 49%
Optical Polarization and Ellipsometry
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